def test_remove(self):
m = make_degenerate_solid_phase_model()
variables = list(m.component_data_objects(pyo.Var))
constraints = list(m.component_data_objects(pyo.Constraint))
igraph = IncidenceGraphInterface(m)
var_dmp, con_dmp = igraph.dulmage_mendelsohn()
var_con_set = ComponentSet(igraph.variables + igraph.constraints)
underconstrained_set = ComponentSet(var_dmp.unmatched +
var_dmp.underconstrained)
self.assertIn(m.flow_comp[1], var_con_set)
self.assertIn(m.flow_eqn[1], var_con_set)
self.assertIn(m.flow_comp[1], underconstrained_set)
N, M = igraph.incidence_matrix.shape
# flow_comp[1] is underconstrained, but we think it should be
# specified by flow_eqn[1], so we remove these from the incidence
# matrix.
vars_to_remove = [m.flow_comp[1]]
cons_to_remove = [m.flow_eqn[1]]
igraph.remove_nodes(vars_to_remove + cons_to_remove)
var_dmp, con_dmp = igraph.dulmage_mendelsohn()
var_con_set = ComponentSet(igraph.variables + igraph.constraints)
underconstrained_set = ComponentSet(var_dmp.unmatched +
var_dmp.underconstrained)
self.assertNotIn(m.flow_comp[1], var_con_set)
self.assertNotIn(m.flow_eqn[1], var_con_set)
self.assertNotIn(m.flow_comp[1], underconstrained_set)
N_new, M_new = igraph.incidence_matrix.shape
self.assertEqual(N_new, N - len(cons_to_remove))
self.assertEqual(M_new, M - len(vars_to_remove))
def test_degenerate_solid_phase_model(self):
m = make_degenerate_solid_phase_model()
variables = list(m.component_data_objects(pyo.Var))
constraints = list(m.component_data_objects(pyo.Constraint))
igraph = IncidenceGraphInterface()
var_dmp, con_dmp = igraph.dulmage_mendelsohn(variables, constraints)
underconstrained_vars = ComponentSet(m.flow_comp.values())
underconstrained_vars.add(m.flow)
underconstrained_cons = ComponentSet(m.flow_eqn.values())
self.assertEqual(len(var_dmp[0] + var_dmp[1]),
len(underconstrained_vars))
for var in var_dmp[0] + var_dmp[1]:
self.assertIn(var, underconstrained_vars)
self.assertEqual(len(con_dmp[2]), len(underconstrained_cons))
for con in con_dmp[2]:
self.assertIn(con, underconstrained_cons)
overconstrained_cons = ComponentSet(m.holdup_eqn.values())
overconstrained_cons.add(m.density_eqn)
overconstrained_cons.add(m.sum_eqn)
overconstrained_vars = ComponentSet(m.x.values())
overconstrained_vars.add(m.rho)
self.assertEqual(len(var_dmp[2]), len(overconstrained_vars))
for var in var_dmp[2]:
self.assertIn(var, overconstrained_vars)
self.assertEqual(len(con_dmp[0] + con_dmp[1]),
len(overconstrained_cons))
for con in con_dmp[0] + con_dmp[1]:
self.assertIn(con, overconstrained_cons)
def test_remove(self):
model = make_gas_expansion_model()
igraph = IncidenceGraphInterface(model)
n_eqn = len(list(model.component_data_objects(pyo.Constraint)))
matching = igraph.maximum_matching()
values = ComponentSet(matching.values())
self.assertEqual(len(matching), n_eqn)
self.assertEqual(len(values), n_eqn)
variable_set = ComponentSet(igraph.variables)
self.assertIn(model.F[0], variable_set)
self.assertIn(model.F[2], variable_set)
var_dmp, con_dmp = igraph.dulmage_mendelsohn()
underconstrained_set = ComponentSet(var_dmp.unmatched +
var_dmp.underconstrained)
self.assertIn(model.F[0], underconstrained_set)
self.assertIn(model.F[2], underconstrained_set)
N, M = igraph.incidence_matrix.shape
# Say we know that these variables and constraints should
# be matched...
vars_to_remove = [model.F[0], model.F[2]]
cons_to_remove = (model.mbal[1], model.mbal[2])
igraph.remove_nodes(vars_to_remove, cons_to_remove)
variable_set = ComponentSet(igraph.variables)
self.assertNotIn(model.F[0], variable_set)
self.assertNotIn(model.F[2], variable_set)
var_dmp, con_dmp = igraph.dulmage_mendelsohn()
underconstrained_set = ComponentSet(var_dmp.unmatched +
var_dmp.underconstrained)
self.assertNotIn(model.F[0], underconstrained_set)
self.assertNotIn(model.F[2], underconstrained_set)
N_new, M_new = igraph.incidence_matrix.shape
self.assertEqual(N_new, N - len(cons_to_remove))
self.assertEqual(M_new, M - len(vars_to_remove))
